Organizations struggle to provide consistent data definitions and business logic across various business intelligence (BI) and AI tools, leading to discrepancies, untrusted insights, and inefficient data workflows. Traditional data silos and the need for extensive data movement further complicate the process of delivering unified and governed data access to end-users.

AtScale offers a universal semantic layer platform that connects directly to diverse data sources, enabling users to access and analyze data using familiar business terms within their preferred BI and AI tools. By defining metrics, dimensions, and relationships in a central location, AtScale ensures consistent KPIs and reusable data models across the organization, eliminating data discrepancies and delivering accurate, trusted results. The platform supports live data access without requiring data movement, while automated query performance tuning ensures "speed-of-thought" analytics. AtScale also provides business context to AI models, improving the accuracy of natural language queries and enabling text-to-SQL generation.

Universal semantic layer that connects to various data sources without data movement

Consistent metrics and reusable data models across all BI and AI tools

Automated query performance tuning for fast analytics

Multi-dimensional business logic support for complex business concepts

Support for SQL, MDX, DAX, Python, and REST protocols

Integration with LLMs to provide business context for GenAI and text-to-SQL applications

Code and no-code solutions for data modeling, fostering collaboration between data engineers and business analysts

AtScale targets enterprises seeking to provide consistent, governed, and high-performance data access to business analysts, data scientists, and other data consumers across various BI, analytics, and AI applications.